Sergiu Oprea

University of Turku, Social Sciences, Undergraduate

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Estimating Context Aware Human-Object Interaction Using Deep Learning-Based Object Recognition Architectures

16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021), 2021

In this work, we propose an architecture for predicting plausible person-object interactions base... more In this work, we propose an architecture for predicting plausible person-object interactions based on image visible objects and room recognition. First of all, the system detects objects in the video using a popular framework named "YOLO" (You Only Look Once) and associates each object with their possible interactions. Then, making use of a convolutional neural network, our algorithm recognizes which is the room that appears in the image and filters possible context aware human-object interactions. The main purpose of this project is helping people with memory failures to do perform daily activities. Many people have problems carrying out actions that can be natural for the rest. With the aim to assist them, we are interested in the development of methods which allow remembering them the actions they may have forgotten.

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A visually realistic grasping system for object manipulation and interaction in virtual reality environments

Computers & Graphics, 2019

Interaction in virtual reality (VR) environments is essential to achieve a pleasant and immersive... more Interaction in virtual reality (VR) environments is essential to achieve a pleasant and immersive experience. Most of the currently existing VR applications, lack of robust object grasping and manipulation, which are the cornerstone of interactive systems. Therefore, we propose a realistic, flexible and robust grasping system that enables rich and real-time interactions in virtual environments. It is visually realistic because it is completely user-controlled, flexible because it can be used for different hand configurations, and robust because it allows the manipulation of objects regardless their geometry, i.e. hand is automatically fitted to the object shape. In order to validate our proposal, an exhaustive qualitative and quantitative performance analysis has been carried out. On the one hand, qualitative evaluation was used in the assessment of the abstract aspects such as: hand movement realism, interaction realism and motor control. On the other hand, for the quantitative evaluation a novel error metric has been proposed to visually analyze the performed grips. This metric is based on the computation of the distance from the finger phalanges to the nearest contact point on the object surface. These contact points can be used with different application purposes, mainly in the field of robotics. As a conclusion, system evaluation reports a similar performance between users with previous experience in virtual reality applications and inexperienced users, referring to a steep learning curve.

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Simple and Digital Implementation of PI Controller Used in Voltage-Mode Control

2018 10th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), 2018

This paper contains a solution for a digital PI controller implemented in a synchronous Buck conv... more This paper contains a solution for a digital PI controller implemented in a synchronous Buck converter used in Constant Voltage configuration. In such applications, a digital PI controller can replace a traditional PI compensation network made with analog components. This is an approachable solution because Proportional and Integral blocks can be easily defined following a transfer function which can tune the respectively coefficients until a stable DC/DC converter is obtained. The PI terms can be digitally implemented using a microcontroller, and then added to the entire system which must provide an adequate response time, maintain system stability and reduce the output voltage steady-state error. A closed loop control system simulation will confirm the above statements. The main advantage of the digital PI control is that no additional analog components are required, resulting in a higher level of integration, also device calibration can be done more smoothly.

Sergiu Oprea

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